Tech jobs
Job listings
Senior Data Engineer (Microsoft Fabric & Azure Data Platform)
Build and optimize cloud-native data pipelines using Microsoft Fabric, Azure Databricks, and PySpark to deliver scalable data solutions for enterprise clients.
Data Engineer - 12 month fixed term contract
Build and maintain scalable ETL/ELT pipelines using Microsoft Fabric, Azure Data Factory, and Python to transform enterprise data into clean, analytics-ready datasets.
Data Engineer - Python - Quant Finance
Builds and maintains mission-critical ETL/ELT pipelines for trading/research data in Python, collaborating with traders to align datasets with macro/commodity strategies.
Data Engineer - Azure, DataBricks, PySpark
Build and maintain cloud data pipelines on Azure and Databricks using Python, PySpark and SQL to power analytics and decision-making for a London insurer.
Scientific Data Engineer - Product Safety
Build and maintain scalable data pipelines and Databricks solutions to transform scientific datasets for regulatory compliance and product safety in agriculture.
Snowflake / Python Data Engineer (Contract) – London
Build and own a Snowflake-based Data Lakehouse: design Snowflake architecture, write Python/SQL pipelines, and set up CI/CD for reliable, scalable data ingestion and analytics.
Data Engineer: Salesforce Integrations & APIs
Designs and maintains Salesforce data integrations and ETL/ELT pipelines to keep systems synchronized and data accurate.
Data Engineer (Microsoft Fabric / Azure)
Builds and maintains scalable data pipelines and analytics solutions using Microsoft Fabric, Azure Synapse, and Power BI to deliver business insights.
Senior Data Engineer: Tick Data & ELT Platform
Senior Data Engineer builds ELT pipelines and streaming platforms for a systematic hedge fund, consolidating legacy systems with Python and SQL.
Data Platform Engineer II - ETL Pipelines - Remote
Build and maintain scalable ETL/ELT pipelines and data models in Snowflake, BigQuery, and Hive using Java and Python to power Tripadvisor’s travel platform.
Hybrid Data Engineer — Azure Data Stack & Lakehouse
Design and maintain scalable ETL/ELT pipelines on Azure and Cloudera, build streaming pipelines with Event Hubs and KQL, and optimize data across bronze/silver/gold layers.
Senior Data Engineer - Real-Time Pipelines on Azure (SC)
Designs and builds secure, scalable data pipelines on Azure, integrating on-premises systems to power analytics and real-time decision-making using Python and ETL/ELT workflows.
DevOps Consultant - Databricks
Build and maintain secure, scalable Databricks data platforms on AWS, automating ELT/ETL pipelines with PySpark, Spark, Kafka and CI/CD to deliver reliable data products.
Senior Data Engineer: Data Platform DevOps & Architecture
Senior Data Engineer to modernize analytics infrastructure by building an Azure-based data platform with DevOps, automated pipelines, and scalable architecture using Python, SQL, and Azure services.
Lead Data Engineer / Data Tech Lead
Lead a team to design and deliver scalable data platforms, pipelines, and warehouses using cloud tools like AWS/Azure/GCP, while mentoring engineers and shaping best practices for reliable, secure data solutions.
Senior Data Engineer (Azure)
Build and secure a modern Azure-based data platform with Databricks, ETL/ELT pipelines, and governance for regulated environments.
Azure Data Engineer - Fabric
Design and implement Azure-based data pipelines and warehouses using Fabric, Synapse, and Data Factory to enable real-time reporting and analytics for UK clients.
Microsoft Fabric Data Engineer
Build and maintain scalable data pipelines and reports using Microsoft Fabric, Azure Synapse, and Power BI to turn raw data into actionable insights for clients.
Remote Azure Data Engineer (Contract)
Build and optimize Azure-based data pipelines and warehouses using Synapse Analytics and ADF, ensuring scalable, reliable data flows for analytics and reporting.
Data Engineer: Data Lake & Pipelines (Hybrid/Remote)
Build and maintain data pipelines for a corporate data lake and platform, ensuring accurate data collection, transformation, and security for reporting and analytics.